Thursday, July 10, 2014

How to Study a cMOOC: Part 3 of a list for #CLMOOC

So I'm closely reading Dillenbourg's 1999 introduction to collaborative learning to see what guidance it may provide for studying cMOOCs such as Rhizo14 and CLMOOC. Dillenbourg's first point about looking at collaborative learning from different scales strikes me as most helpful, but his second point about defining learning at best provides negative examples: what not to do. His third and final point about defining collaboration also seems to be a negative example of how not to approach cMOOCs. Let's see what Dillenbourg has to say.

Dillenbourg looks at collaboration from four points of view, or on four different scales:

situation,

interactions,

mechanisms, and

effects.

I like that he keeps his commitment to working with any complex system from a variety of scales. This is a key, I think, to looking at any cMOOC. But he is clearly talking about collaboration and not cooperation, an issue that Jenny Mackness opened for me and that I addressed in my last post. This suggests to me that his approach to collaboration may be another negative example for me.

Collaborative Situations - The first way to explore collaboration, Dillenbourg says, is as a situation in which agents:

are more or less at the same level: collaboration as a situation requires a symmetry in which all collaborating agents have similar freedom and ability to act, a similar level of knowledge, and similar status within the group. It seems that asymmetry disrupts collaboration. If you know significantly more than I, then you may try boss me, breaking the collaboration. A collaborative group, then, requires a certain homogeneity, a red flag for rhizomatic, cMOOC enthusiasts.

can perform the same actions: again an implied homogeneity among collaborative agents. No one is particularly more skillful than the others, though Dillenbourg does allow for some specialization of skills within the collaborative group. Too much, though, undermines the collaborative ethos, it seems.

have a common goal: collaboration requires a shared goal, whereas competition requires conflicting goals (this either/or approach leaves out cooperation altogether, it seems to me). Shared goals can partially assigned at the outset of collaboration, but also depends on the collaborating agents negotiating their shared goal, and in the process becoming aware of their mutual dependence.

work together: Dillenbourg finally mentions cooperation, but I don't think it helps much. He notes that some scholars use the terms interchangeably, while some distinguish them: cooperation is when group agents "split the work, solve sub-tasks individually and then assemble the partial results into the final output," and collaboration is when agents "do the work together." I don't think Jenny Mackness or Stephen Downes would favor this definition of cooperation.

Collaborative Interactions - The second way Dillenbourg looks at collaboration is by the nature of a group's interactions:

interactivity: collaborative interactions are, well, interactive, which seems intuitively obvious, but Dillenbourg defines the degree of interactivity not by frequency but by the intensity of the interactions, by the degree to which the interactions influence the peers' cognitive processes. This is an interesting approach to interactivity, but as Dillenbourg notes, devilishly difficult to measure.

synchronicity: collaborative interactions are synchronous says Dillenbourg. Collaborators expect their peers to "wait for [their] message and … process the message as soon as it is delivered." Asynchronous communication is out for collaboration, but I see no advantage to Dillenbourg's definition here. Linux, for instance, is a collaborative effort that seems to thrive on both synchronous and asynchronous communication. I hope Dillenbourg has dropped this.

negotiability: finally, collaborative interactions are negotiated rather than mandated. Negotiation implies for Dillenbourg space among the collaborators for negotiation and misunderstanding, a space for constructing shared meaning regarding the project and its execution.

Collaborative Processes - The third way Dillenbourg explores collaboration is by the mechanisms that enable group interactions and learning. He starts with those mechanisms that are common to individual learning but also occur in group learning: induction, cognitive load, self-explanation, and conflict. He then talks about those mechanisms more closely associated with group learning: internalization, appropriation, and mutual modeling.

Collaborative Effects - The final way Dillenbourg considers collaboration is through its effects on learning, usually as a measurement of individual task performance. He notes two main problems with measuring the effects of collaborative learning:

It is difficult to isolate in a collaborative situation, with its many contexts and interactions, the specific causes of any identifiable learning.

It is difficult to infer the degree of group learning from measurements of individual learning.

So what does this have to say about how the Rhizo14 auto-ethnography group, for instance, should go about looking at Rhizo14?

On the positive side, researchers will benefit from a multi-scale, multi-perspective approach to exploring any complex, multi-scale, self-organizing system such as a cMOOC. This is not to suggest that any single researcher or research effort must attempt to cover all scales and aspects of a cMOOC, but it does suggest that a research effort will benefit if it creates ample space for multiple approaches to the same system.

I am also interested in Dillenbourg's characterization of interactivity not as a quantity but as a quality. He doesn't measure the number of engagements so much as the degree to which an engagement affects a colleague's cognitive processes. This reminds me of Deleuze and Guattari's decalcomania, one of the six features of the rhizome and perhaps the feature least mentioned and discussed by others. Perhaps it is the least understood, or least impressive, but I think that is unfortunate. Decalcomania appears to me to be the process by which memes (a term coined by Richard Dawkins about the same time Deleuze and Guattari were writing A Thousand Plateaus, so perhaps unknown to them) spread through a system. It is a kind of staining. One is stained through an engagement with another and an exchange of energy, matter, information, organization, or all four. Dillenbourg rightly notes that this view of interactivity is difficult to measure and quantify, but everyone in a cMOOC experiences it: an idea emerges somewhere in the network and passes along tweets, posts, and discussions to many others in the network and outside it. Some stain, some don't. The more who stain, the more pervasive and powerful the meme and the more likely it is to spread more. There is a network power law at work here and definitely network propagation (decalcomania) which cMOOC investigators should keep in mind.

Then, Dillenbourg's take on the negotiability of collaborative interactions may hold as well for cooperative networks, but I have to think much more about this. Something wants me to frame the notion of negotiated social contracts in a different way, but I'm not ready to do it now, so I'll just pass.

Finally, Dillenbourg's thoughts about collaborative processes, the mechanisms that enable collaborative learning, seem equally relevant to cooperation as to collaboration. I don't think Dillenbourg was attempting to be exhaustive in the processes he discusses, and I see no reason why induction, cognitive load, self-explanation, conflict, internalization, appropriation, and mutual modeling would not play well in cooperative learning. Though it is possible that other mechanisms that I cannot think of just now play better in cooperative learning than in collaborative learning.

On the negative side, Dillenbourg's 1999 delineation of collaboration and cooperation seems, to me, to miss the concepts emerging in current conversations about cMOOCs. Jenny Mackness pointed to Stephen Downes' careful explanation about the differences between the two, and Dillenbourg's use of cooperation in this article does not match so well. Downes' distinction hinges on the differences between groups and networks and the role of the individual in each. In collaborative groups, individuals are subsumed under the group, becoming a part of the group, while in cooperative networks the individual is not subsumed by the collection of agents; rather, the network is an emergent property of the collection of individuals and their interactions. Dillenbourg's use of cooperation as mostly a difference in distributing the workload of the group misses most of the richness of Downes' use and affords very little help in understanding cMOOCs.

On the other hand, Dillenbourg's use of the term collaboration seems reasonably consistent with Downes' use, so I assume that they are mostly talking about the same kind of system. Thus, I take away from Dillenbourg's article some approaches not to use with cMOOCs. For instance, collaborative groups for Dillenbourg and Downes imply a certain homogeneity in the collection of individuals: similar capabilities, actions, goals, and affordances, especially similar languages and technologies. cMOOCs, on the other hand, are open to heterogeneity, and any effort to explore and map a cMOOC must account for this heterogeneity, this openness to divergent actions, aims, abilities, and affordances. For instance, lurkers have negative roles in a collaborative group and are often eliminated, but they can play a very productive role in a cooperative network, or rhizomatic community.

Dillenbourg's assertion that collaborative groups rely on synchronous communication doesn't match my understanding of what happens online in either collaborative groups or cooperative networks. I take the Linux project to be a monstrously successful collaboration, and I'm confident that group uses both synchronous and asynchronous communications to collaborate. I know that cooperative networks such as cMOOCs use both, so I see no need to limit either collaboration or cooperation to one or the other types of communication. I do see, however, a need to study how and why agents will chose one over the other and what each affords the agents in a system.

Finally, Dillenbourg's handling of collaborative effects seems hampered by its focus on local causality. Both online and f2f collaborative and cooperative systems can be explored and explained as much, perhaps more, by circular and global causalities as by local causalities. Self-organizing systems can seldom be explained by the local pushes of the one-to-one interactions among its constituent agents. Rather, one must include the global pull of the larger, emerging system as it seeks a comfortable function and form within its ecosystem. Likewise, the learning that emerges within a complex system must include circular causalities which account for the continuous flow and feedback of information, energy, and organization among the individual agents and between the emerging system and its ecosystem. To grasp a cMOOC, our field of reality must be enlarged. For instance, the Rhizo14 auto-ethnography cannot simply ask if an instructional technique employed by Dave Cormier led to a specific learning in any of the Rhizo14 participants, as we might do in a traditional classroom. Rather, the group should expand its field to explore how Rhizo14 emerged and self-organized, shaping and ordering itself around various conversational spaces such as Facebook, Twitter, P2PU, blogs, and G+. What global causes pulled Rhizo14 into this particular organization? The group should explore how one conversation fed into another conversation, reshaping both conversations in a mutually causal feedback loop. What circular causes looped Rhizo14 into poetic expressions? Did DS106 and CLMOOC feed into Rhizo14? Has Rhizo14 fed back into those systems? These are the kinds of questions that must frame any discussion of a complex, multi-scale system, I think.